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Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2024年第10期21卷 1959页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

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LaG-DESIQUE: A local-and-global blind image quality evaluator without training on human opinion scores 6th

LaG-DESIQUE: A local-and-global blind image quality evaluato...

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6th CCF Academic Conference on Big Data, CCF Big Data 2018

作者： Liu, Ruyi Zhang, Yi Chandler, Damon M. Miao, Qiguang Liu, Tiange School of Computer Science and Technology Xidian University XianShaanxi710071 China Xian Key Laboratory of Big Data and Intelligent Vision XianShaanxi710071 China School of Electronic and Information Engineering Xian Jiaotong University XianShaanxi710049 China Department of Electrical and Electronic Engineering Shizuoka University HamamatsuShizuoka432-8561 Japan School of Information Science and Engingeering Yanshan University QinhuangdaoHebei066004 China

ISBN: (纸本)9789811329210

This paper extends our previous DESIQUE [1] algorithm to a local-and-global way (LaG-DESIQUE) to blindly measure image quality without training on human opinion scores. The local DESIQUE extracts block-based log-derivative features and evaluates image quality through measuring the multivariate Gaussian distance between selected natural and test image patches. The global DESIQUE extracts image-based log-derivative features and image quality is estimated based on a two-stage framework, which was trained on a set of regenerated distorted images with their quality scores estimated by MAD [2] algorithm. The overall quality is the weighted average of local and global DESIQUE scores. Test on several image databases demonstrates that LaG-DESIQUE performs competitively well in predicting image quality. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Image quality

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The limits and potentials of deep learning for robotics

arXiv

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arXiv 2018年

作者： Sünderhauf, Niko Brock, Oliver Scheirer, Walter Hadsell, Raia Fox, Dieter Leitner, Jürgen Upcroft, Ben Abbeel, Pieter Burgard, Wolfram Milford, Michael Corke, Peter Brisbane Australia Robotics and Biology Laboratory Technische Universität Berlin Germany Department of Computer Science and Engineering University of Notre Dame IN United States DeepMind London United Kingdom Paul G. Allen School of Computer Science & Engineering University of Washington WA United States Oxbotica Ltd. Oxford United Kingdom UC Berkeley Department of Electrical Engineering and Computer Sciences CA United States Department of Computer Science University of Freiburg Germany

The application of deep learning in robotics leads to very specific problems and research questions that are typically not addressed by the computer vision and machine learning communities. In this paper we discuss a number of robotics-specific learning, reasoning, and embodiment challenges for deep learning. We explain the need for better evaluation metrics, highlight the importance and unique challenges for deep robotic learning in simulation, and explore the spectrum between purely data-driven and model-driven approaches. We hope this paper provides a motivating overview of important research directions to overcome the current limitations, and help fulfill the promising potentials of deep learning in robotics. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep learning

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Design, Development and Control of a Three Flexible-Fingers Gripper Based On Hand Gesture

Design, Development and Control of a Three Flexible-Fingers ...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Rasoul Sadeghian Pooyan Sedigh Parastoo Azizinezhad Shahrooz Shahin Mehdi Tale Masouleh Human and Robot Interaction Laboratory Tehran Iran Department of Biomedical Engineering Science and Research Branch Islamic Azad University Tehran Iran Faculty of Electrical and Computer Science Robotic Engineering Tehran North Branch Islamic Azad University Tehran Iran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781728101286;9781728101279

In this paper, the process of design, and construction of a flexible gripper with three fingers is presented. The fingers of the proposed gripper are fabricated using a 3D printing device. The gripper is controlled remotely by an autonomous glove which is designed to help people with disability. In order to ameliorate the movement accuracy of the gripper a Fuzzy-PID controller is implemented on the system. The result of experimental tests demonstrate a decrease of the gripper movement error to less than 2 degrees in average. An ultrasonic sensor is set on the gripper's body to improve the grasping process by detecting the distance of the object to the gripper. The fabricated fingers are flexible and provides the ability of grasping the objects with irregular shapes. The experimental test approves the significant performance of the gripper in term of grasping complex shape objects.

关键词： Grippers Grasping Flexible printed circuits Robot sensing systems Shape Kalman filters

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Small core FBG-based temperature compensated ‘smart’ contact lens for effective intraocular pressure measurement

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Measurement: Sensors 2019年 1卷

作者： Chen, Ye Wang, Jun Zhao, Yin Liu, Xiao-Jun Zhang, Hong Murdoch, Ian Hull, Chris Barbur, John Sun, Tong Grattan, KennethT.V. Department of Electrical & Electronic Engineering School of Mathematics Computer Science & Engineering City University of London Northampton Square LondonEC1V 0HB United Kingdom State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Ophthalmology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan430030 China Institute of Ophthalmology University College London Bath Street LondonEC1V 9EL United Kingdom Centre for Applied Vision Research School of Health Sciences City University of London LondonEC1R 1UB United Kingdom

In this work, a small core, Fibre Bragg Grating (FBG)-based smart contact lens for intraocular pressure (IOP) measurement has been demonstrated. Further, an integral temperature compensation mechanism has been developed and included in the sensor design, allowing it to offer good long-term measurement capability while allowing for any local temperature fluctuations. The sensitivity of the device has been shown to be 12.9 p.m./mmHg, yielding good repeatability in tests carried out. Such a small core fibre, FBG-based smart contact lens shows significant potential for improving the management and therapy of glaucoma, the second most common cause of preventable blindness in the world. © 2019

关键词： Wearable sensors

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Morphological geodesic active contour based automatic aorta segmentation in thoracic CT images

Morphological geodesic active contour based automatic aorta ...

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International Conference on computer vision and Image Processing, CVIP 2016

作者： Dasgupta, Avijit Mukhopadhyay, Sudipta Mehre, Shrikant A. Bhattacharyya, Parthasarathi Computer Vision and Image Processing Laboratory Department of Electronics and Electrical Communication Engineering Indian Institute of Technology Kharagpur West Bengal721302 India Institute of Pulmocare & Research KolkataWest Bengal700156 India

ISBN: (纸本)9789811021060

Automatic aorta segmentation and quantification in thoracic computed tomography (CT) images is important for detection and prevention of aortic diseases. This paper proposes an automatic aorta segmentation algorithm in both contrast and non-contrast CT images of thorax. The proposed algorithm first detects the slice containing the carina region. Circular Hough Transform (CHT) is applied on the detected slice to localize ascending and descending aorta (circles with lowest variances) followed by a morphological geodesic active contour to segment the aorta from CT stack. The dice similarity coefficients (DSC) between the ground truth and the segmented output were found to be 0.8845 ± 0.0584 on LIDC-IDRI dataset. © Springer Science+Business Media Singapore 2017.

关键词： Image segmentation

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Minimum uncertainty latent variable models for robot recognition of sequential human activities

Minimum uncertainty latent variable models for robot recogni...

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2017 IEEE International Conference on robotics and Automation, ICRA 2017

作者： Han, Fei Reardon, Christopher Parker, Lynne E. Zhang, Hao Human-Centered Robotics Lab Department of Computer Science Colorado School of Mines GoldenCO80401 United States US Army Research Laboratory AdelphiMD20783 United States Distributed Intelligence Laboratory Department of Electrical Engineering and Computer Science University of Tennessee TN37996 United States

ISBN: (纸本)9781509046331

Recognition of sequential human activities, such as 'sitting down' and 'standing up', is a common but challenging problem in human-robot interaction, which requires modeling their underlying temporal patterns. Although previous sequence modeling methods, such as Hidden Conditional Random Fields (HCRFs), demonstrated satisfactory recognition accuracy, they do not explicitly model the uncertainty in underlying temporal patterns, which can provide valuable information to characterize sequential activities. To address this problem, we introduce a novel Minimum Uncertainty HCRF (MU, or μHCRF). Different from traditional HCRF-based techniques that only utilize the negative log-likelihood of the categories' conditional probability as the loss function, the proposed μ-HCRF also introduces a regularization term to model the underlying temporal pattern of the latent variables. As another theoretical contribution, we provide a derivation to show that the formulated problem has a closed-form solution, and prove that inference of the proposed μHCRF is tractable. Extensive empirical study is performed to evaluate our approach, using four public benchmark datasets. Experimental results have shown that our μHCRFs outperform previous techniques and achieve state-of-the-art performance on human activity recognition, especially on sequential activities. © 2017 IEEE.

关键词： Human robot interaction

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Mobile robot localisation and navigation using LEGO NXT and ultrasonic sensor

arXiv

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arXiv 2018年

作者： Liu, Yanan Fan, Rui Yu, Bin Junaid Bocus, M. Liu, Ming Ni, Hepeng Fan, Jiahe Mao, Shixin Bristol Robotics Laboratory University of Bristol Bristol United Kingdom Robotics and Multi-Perception Laboratory Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Department of Electrical and Electronic Engineering University of Bristol BristolBS8 1UB United Kingdom School of Mechanical Engineering Shandong University Jinan250061 China School of Communication Engineering Jilin University Changchun130000 China Shenzhen Sanhang Industrial Technology Research Institute Shenzhen518000 China

Mobile robots are becoming increasingly important both for individuals and industries. Mobile robotic technology is not only utilised by experts in this field but is also very popular among amateurs. However, implementing a mobile robot to perform tasks autonomously can be expensive because of the need for various types of sensors and the high price of robot platforms. Hence, in this paper we present a mobile robot localisation and navigation system which uses a LEGO ultrasonic sensor in an indoor map based on the LEGO MINDSTORM NXT. This provides an affordable and ready-to-use option for most robot fans. In this paper, an effective method is proposed to extract useful information from the distorted readings collected by the ultrasonic sensor. Then, the particle filter is used to localise the robot. After robot's position is estimated, a sampling-based path planning method is proposed for the robot navigation. This method reduces the robot accumulative motion error by minimising robot turning times and covering distances. The robot localisation and navigation algorithms are implemented in MATLAB. Simulation results show an average accuracy between 1 and 3 cm for three different indoor map locations. Furthermore, experiments performed in a real setup show the effectiveness of the proposed methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Mobile robots

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The dynamic interactions between chemotherapy drugs and plasmid DNA investigated by atomic force microscopy

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Science China Materials 2017年第3期60卷 269-278页

作者：李密刘连庆肖秀斌席宁王越超 State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Department of Lymphoma Affiliated Hospital of Military Medical Academy of Sciences Department of Electrical and Computer Engineering Michigan State University

The advent of atomic force microscopy （AFM） provides a powerful tool for imaging individual DNA molecules. Chemotherapy drugs are often related to DNAs. Though many specific drug-DNA interactions have been observed by AFM, knowledge about the dynamic interactions between chemotherapy drugs and plasmid DNAs is still scarce. In this work, AFM was applied to investigate the nanoscale interactions between plasmid DNAs and two commercial chemotherapy drugs （methotrexate and cisplatin）. Plasmid DNAs were immobilized on mica which was coated by silanes in advance. AFM imaging distinctly revealed the dynamic changes of single plasmid DNAs after the stimulation of methotrexate and cisplatin. Geometric features of plasmid DNAs were extracted from AFM images and the statistical results showed that the geometric features of plasmid DNAs changed significantly after the stimulation of drugs. This research provides a novel idea to study the actions of chemotherapy drugs against plasmid DNAs at the single-molecule level.

关键词： atomic force microscopy plasmid DNA drug methotrexate cisplatin

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UAV navigation with computer vision - Flight testing a novel visual odometry technique

UAV navigation with computer vision - Flight testing a novel...

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AIAA Guidance, Navigation, and Control Conference, 2018

作者： DePaola, Rick Chimento, Charlie W. Brink, Kevin M. Willis, Andrew R. Anderson, Michael L. Department of Engineering Mechanics United States Air Force Academy USAFA 2354 Fairchild Dr. CO80840 United States Munitions Directorate Air Force Research Laboratory Eglin AFB 101 W. Eglin Blvd. FL32542 United States Electrical and Computer Engineering Dept. University of North Carolina at Charlotte 9201 University City Blvd. CharlotteNC28223 United States

ISBN: (数字)9781624105265

ISBN: (纸本)9781624105265

Numerous applications for Unmanned Air Vehicles (UAVs) have created research needs that seek to improve their autonomy, safety and mission performance while simultaneously reducing their operating costs. One critical need for many applications is autonomous navigation of UAVs indoors, or in other environments lacking Global Positioning System (GPS) location information. A leading solution is to use visual sensors, i.e., cameras, and Simultaneous Localization and Mapping (SLAM) to track the UAV’s pose referred to as visual odometry. In this work, a visual odometry algorithm is flight tested and evaluated that can aid a filter in tracking vehicle pose by providing delta-pose estimates obtained from sequential pairs of Red Green Blue Depth (RGBD) camera images. This evaluation is focused on a recently proposed approach that simultaneously estimates delta-pose and an associated, dynamic uncertainty (covariance) in real-time. This contrasts with prior work that typically assigns a fixed covariance to RGBD-based odometry measurements throughout a flight. Analysis leverages real-time flight data and a motion capture system to evaluate the consistency of the estimated covariance values with the end goal of facilitating better integration of sensor measurements into navigation algorithms. Results suggest that the dynamic covariance estimates generated correspond well with the actual error and provide a significant improvement over state-of-the-art for RGBD odometry integration with fused-state navigational systems. © 2018 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Operating costs

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